Use of Megasphaera elsdenii NCIMB41125 as a probiotic for early-lactation dairy cows: effects on rumen pH and fermentation patterns

Multiparous rumen-fistulated Holstein cows were fed, from d 1 to 28 post-calving, an ad libitum TMR containing (g/kg DM) grass silage (196), corn silage (196), wheat (277), soybean meal (100), and other feeds (231) with CP, NDF, starch and water soluble carbohydrate concentrations of 176, 260, 299 and 39 g/kg DM respectively and ME of 12.2 MJ/kg DM. Treatments consisting of a minimum of 1010 cfu Megasphaera elsdenii NCIMB 41125 in 250 ml solution (MEGA) or 250 ml of autoclaved M. elsdenii (CONT) were administered via the rumen cannula on d 3 and 12 of lactation (n=7 per treatment). Mid-rumen pH was measured every 15 minutes and eating and ruminating behavior was recorded for 24 h on d 2, 4, 6, 8, 11, 13, 15, 17, 22 and 28. Rumen fluid for VFA and lactic acid (LA) analysis was collected at 11 timepoints on each of d 2, 4, 6, 13 and 15. Data were analysed as repeated measures using the Glimmix (LA data) or Mixed (all other data) procedures of SAS with previous 305 d milk yield and d 2 measurements as covariates where appropriate. Milk yield was higher (CONT 43.0 vs MEGA 45.4 ±0.75 kg/d, P=0.051) and fat concentration was lower (CONT 45.6 vs MEGA 40.4 ±1.05 g/kg, P=0.005) in cows that received MEGA. Time spent eating (263 ±15 min/d) and ruminating (571 ±13 min/d), DM intake (18.4 ±0.74 kg/d), proportion of each 24 h period with rumen pH below 5.6 (3.69 ±0.94 h) and LA concentrations (2.00 mM) were similar (P>0.327) across treatments. Ruminal total VFA concentration (104 ±3 mM) was similar (P=0.404) across treatments, but a shift from acetate (CONT 551 vs MEGA 524 ±14 mmol/mol VFA, P=0.161) to propionate production (CONT 249 vs MEGA 275 ±11 mmol/mol VFA, P=0.099) meant that the acetate:propionate ratio (CONT 2.33 vs MEGA 1.94 ±0.15) was reduced (P=0.072) in cows that received MEGA. This study provides evidence that supplementation of early lactation dairy cows with MEGA alters rumen fermentation patterns in favour of propionate, with potential benefits for animal health and productivity.

Optimal control of nonlinear differential algebraic equation systems

A novel iterative procedure is described for solving nonlinear optimal control problems subject to differential algebraic equations. The procedure iterates on an integrated modified linear quadratic model based problem with parameter updating in such a manner that the correct solution of the original non-linear problem is achieved. The resulting algorithm has a particular advantage in that the solution is achieved without the need to solve the differential algebraic equations . Convergence aspects are discussed and a simulation example is described which illustrates the performance of the technique. 1. Introduction When modelling industrial processes often the resulting equations consist of coupled differential and algebraic equations (DAEs). In many situations these equations are nonlinear and cannot readily be directly reduced to ordinary differential equations.

Nonlinear data assimilation in geosciences: an extremely efficient particle filter

Almost all research fields in geosciences use numerical models and observations and combine these using data-assimilation techniques. With ever-increasing resolution and complexity, the numerical models tend to be highly nonlinear and also observations become more complicated and their relation to the models more nonlinear. Standard data-assimilation techniques like (ensemble) Kalman filters and variational methods like 4D-Var rely on linearizations and are likely to fail in one way or another. Nonlinear data-assimilation techniques are available, but are only efficient for small-dimensional problems, hampered by the so-called ‘curse of dimensionality’. Here we present a fully nonlinear particle filter that can be applied to higher dimensional problems by exploiting the freedom of the proposal density inherent in particle filtering. The method is illustrated for the three-dimensional Lorenz model using three particles and the much more complex 40-dimensional Lorenz model using 20 particles. By also applying the method to the 1000-dimensional Lorenz model, again using only 20 particles, we demonstrate the strong scale-invariance of the method, leading to the optimistic conjecture that the method is applicable to realistic geophysical problems. Copyright c 2010 Royal Meteorological Society

A micro-level simulation for the prediction of intention and behaviour

In this contribution we aim at anchoring Agent-Based Modeling (ABM) simulations in actual models of human psychology. More specifically, we apply unidirectional ABM to social psychological models using low level agents (i.e., intra-individual) to examine whether they generate better predictions, in comparison to standard statistical approaches, concerning the intentions of performing a behavior and the behavior. Moreover, this contribution tests to what extent the predictive validity of models of attitude such as the Theory of Planned Behavior (TPB) or Model of Goal-directed Behavior (MGB) depends on the assumption that peoples’ decisions and actions are purely rational. Simulations were therefore run by considering different deviations from rationality of the agents with a trembling hand method. Two data sets concerning respectively the consumption of soft drinks and physical activity were used. Three key findings emerged from the simulations. First, compared to standard statistical approach the agent-based simulation generally improves the prediction of behavior from intention. Second, the improvement in prediction is inversely proportional to the complexity of the underlying theoretical model. Finally, the introduction of varying degrees of deviation from rationality in agents’ behavior can lead to an improvement in the goodness of fit of the simulations. By demonstrating the potential of ABM as a complementary perspective to evaluating social psychological models, this contribution underlines the necessity of better defining agents in terms of psychological processes before examining higher levels such as the interactions between individuals.

An item response analysis of the motor and behavioral subscales of the unified Huntington's disease rating scale in huntington disease gene expansion carriers

Although the Unified Huntington's Disease Rating Scale (UHDRS) is widely used in the assessment of Huntington disease (HD), the ability of individual items to discriminate individual differences in motor or behavioral manifestations has not been extensively studied in HD gene expansion carriers without a motor-defined clinical diagnosis (ie, prodromal-HD or prHD). To elucidate the relationship between scores on individual motor and behavioral UHDRS items and total score for each subscale, a nonparametric item response analysis was performed on retrospective data from 2 multicenter longitudinal studies. Motor and behavioral assessments were supplied for 737 prHD individuals with data from 2114 visits (PREDICT-HD) and 686 HD individuals with data from 1482 visits (REGISTRY). Option characteristic curves were generated for UHDRS subscale items in relation to their subscale score. In prHD, overall severity of motor signs was low, and participants had scores of 2 or above on very few items. In HD, motor items that assessed ocular pursuit, saccade initiation, finger tapping, tandem walking, and to a lesser extent, saccade velocity, dysarthria, tongue protrusion, pronation/supination, Luria, bradykinesia, choreas, gait, and balance on the retropulsion test were found to discriminate individual differences across a broad range of motor severity. In prHD, depressed mood, anxiety, and irritable behavior demonstrated good discriminative properties. In HD, depressed mood demonstrated a good relationship with the overall behavioral score. These data suggest that at least some UHDRS items appear to have utility across a broad range of severity, although many items demonstrate problematic features.

Beyond the technical: a snapshot of energy and buildings research

The past decade has witnessed a sharp increase in published research on energy and buildings. This paper takes stock of work in this area, with a particular focus on construction research and the analysis of non-technical dimensions. While there is widespread recognition as to the importance of non-technical dimensions, research tends to be limited to individualistic studies of occupants and occupant behavior. In contrast, publications in the mainstream social science literature display a broader range of interests, including policy developments, structural constraints on the diffusion and use of new technologies and the construction process itself. The growing interest of more generalist scholars in energy and buildings provides an opportunity for construction research to engage a wider audience. This would enrich the current research agenda, helping to address unanswered problems concerning the relatively weak impact of policy mechanisms and new technologies and the seeming recalcitrance of occupants. It would also help to promote the academic status of construction research as a field. This, in turn, depends on greater engagement with interpretivist types of analysis and theory building, thereby challenging deeply ingrained views on the nature and role of academic research in construction.

Fetal programming effects of testosterone on the reward system and behavioral approach tendencies in humans

BACKGROUND: Sex differences are present in many neuropsychiatric conditions that affect emotion and approach-avoidance behavior. One potential mechanism underlying such observations is testosterone in early development. Although much is known about the effects of testosterone in adolescence and adulthood, little is known in humans about how testosterone in fetal development influences later neural sensitivity to valenced facial cues and approach-avoidance behavioral tendencies. METHODS: With functional magnetic resonance imaging we scanned 25 8-11-year-old children while viewing happy, fear, neutral, or scrambled faces. Fetal testosterone (FT) was measured via amniotic fluid sampled between 13 and 20 weeks gestation. Behavioral approach-avoidance tendencies were measured via parental report on the Sensitivity to Punishment and Sensitivity to Rewards questionnaire. RESULTS: Increasing FT predicted enhanced selectivity for positive compared with negatively valenced facial cues in reward-related regions such as caudate, putamen, and nucleus accumbens but not the amygdala. Statistical mediation analyses showed that increasing FT predicts increased behavioral approach tendencies by biasing caudate, putamen, and nucleus accumbens but not amygdala to be more responsive to positive compared with negatively valenced cues. In contrast, FT was not predictive of behavioral avoidance tendencies, either through direct or neurally mediated paths. CONCLUSIONS: This work suggests that testosterone in humans acts as a fetal programming mechanism on the reward system and influences behavioral approach tendencies later in life. As a mechanism influencing atypical development, FT might be important across a range of neuropsychiatric conditions that asymmetrically affect the sexes, the reward system, emotion processing, and approach behavior.

The effect of nonlinearity in CO2 heating rates on the attribution of stratospheric ozone and temperature changes

An analysis of the attribution of past and future changes in stratospheric ozone and temperature to anthropogenic forcings is presented. The analysis is an extension of the study of Shepherd and Jonsson (2008) who analyzed chemistry-climate simulations from the Canadian Middle Atmosphere Model (CMAM) and attributed both past and future changes to changes in the external forcings, i.e. the abundances of ozone-depleting substances (ODS) and well-mixed greenhouse gases. The current study is based on a new CMAM dataset and includes two important changes. First, we account for the nonlinear radiative response to changes in CO2. It is shown that over centennial time scales the radiative response in the upper stratosphere to CO2 changes is significantly nonlinear and that failure to account for this effect leads to a significant error in the attribution. To our knowledge this nonlinearity has not been considered before in attribution analysis, including multiple linear regression studies. For the regression analysis presented here the nonlinearity was taken into account by using CO2 heating rate, rather than CO2 abundance, as the explanatory variable. This approach yields considerable corrections to the results of the previous study and can be recommended to other researchers. Second, an error in the way the CO2 forcing changes are implemented in the CMAM was corrected, which significantly affects the results for the recent past. As the radiation scheme, based on Fomichev et al. (1998), is used in several other models we provide some description of the problem and how it was fixed.

Preferential dust sources: a geomorphological classification designed and for use in global aerosol models

We present a simple theoretical land-surface classification that can be used to determine the location and temporal behavior of preferential sources of terrestrial dust emissions. The classification also provides information about the likely nature of the sediments, their erodibility and the likelihood that they will generate emissions under given conditions. The scheme is based on the dual notions of geomorphic type and connectivity between geomorphic units. We demonstrate that the scheme can be used to map potential modern-day dust sources in the Chihuahuan Desert, the Lake Eyre Basin and the Taklamakan. Through comparison with observed dust emissions, we show that the scheme provides a reasonable prediction of areas of emission in the Chihuahuan Desert and in the Lake Eyre Basin. The classification is also applied to point source data from the Western Sahara to enable comparison of the relative importance of different land surfaces for dust emissions. We indicate how the scheme could be used to provide an improved characterization of preferential dust sources in global dust-cycle models.

Genetic variation in GABRB3 is associated with Asperger syndrome and multiple endophenotypes relevant to autism.

BACKGROUND: Autism spectrum conditions (ASC) are associated with deficits in social interaction and communication, alongside repetitive, restricted, and stereotyped behavior. ASC is highly heritable. The gamma-aminobutyric acid (GABA)-ergic system has been associated consistently with atypicalities in autism, in both genetic association and expression studies. A key component of the GABA-ergic system is encoded by the GABRB3 gene, which has been previously implicated both in ASC and in individual differences in empathy. METHODS: In this study, 45 genotyped single nucleotide polymorphisms (SNPs) within GABRB3 were tested for association with Asperger syndrome (AS), and related quantitative traits measured through the following tests: the Empathy Quotient (EQ), the Autism Spectrum Quotient (AQ), the Systemizing Quotient-Revised (SQ-R), the Embedded Figures Test (EFT), the Reading the Mind in the Eyes Test (RMET), and the Mental Rotation Test (MRT). Two-loci, three-loci, four-loci haplotype analyses, and one seven-loci haplotype analysis were also performed in the AS case--control sample. RESULTS: Three SNPs (rs7180158, rs7165604, rs12593579) were significantly associated with AS, and two SNPs (rs9806546, rs11636966) were significantly associated with EQ. Two SNP-SNP pairs, rs12438141-rs1035751 and rs12438141-rs7179514, showed significant association with variation in the EFT scores. One SNP-SNP pair, rs7174437-rs1863455, was significantly associated with variation in the MRT scores. Additionally, a few haplotypes, including a 19 kb genomic region that formed a linkage disequilibrium (LD) block in our sample and contained several nominally significant SNPs, were found to be significantly associated with AS. CONCLUSION: The current study confirms the role of GABRB3 as an important candidate gene in both ASC and normative variation in related endophenotypes.

Transient receptor potential ion channels V4 and A1 contribute to pancreatitis pain in mice.

The mechanisms of pancreatic pain, a cardinal symptom of pancreatitis, are unknown. Proinflammatory agents that activate transient receptor potential (TRP) channels in nociceptive neurons can cause neurogenic inflammation and pain. We report a major role for TRPV4, which detects osmotic pressure and arachidonic acid metabolites, and TRPA1, which responds to 4-hydroxynonenal and cyclopentenone prostaglandins, in pancreatic inflammation and pain in mice. Immunoreactive TRPV4 and TRPA1 were detected in pancreatic nerve fibers and in dorsal root ganglia neurons innervating the pancreas, which were identified by retrograde tracing. Agonists of TRPV4 and TRPA1 increased intracellular Ca(2+) concentration ([Ca(2+)](i)) in these neurons in culture, and neurons also responded to the TRPV1 agonist capsaicin and are thus nociceptors. Intraductal injection of TRPV4 and TRPA1 agonists increased c-Fos expression in spinal neurons, indicative of nociceptor activation, and intraductal TRPA1 agonists also caused pancreatic inflammation. The effects of TRPV4 and TRPA1 agonists on [Ca(2+)](i), pain and inflammation were markedly diminished or abolished in trpv4 and trpa1 knockout mice. The secretagogue cerulein induced pancreatitis, c-Fos expression in spinal neurons, and pain behavior in wild-type mice. Deletion of trpv4 or trpa1 suppressed c-Fos expression and pain behavior, and deletion of trpa1 attenuated pancreatitis. Thus TRPV4 and TRPA1 contribute to pancreatic pain, and TRPA1 also mediates pancreatic inflammation. Our results provide new information about the contributions of TRPV4 and TRPA1 to inflammatory pain and suggest that channel antagonists are an effective therapy for pancreatitis, when multiple proinflammatory agents are generated that can activate and sensitize these channels.

Adaptive B-spline neural network based nonlinear equalization for high-order QAM systems with nonlinear transmit high power amplifier

High bandwidth-efficiency quadrature amplitude modulation (QAM) signaling widely adopted in high-rate communication systems suffers from a drawback of high peak-toaverage power ratio, which may cause the nonlinear saturation of the high power amplifier (HPA) at transmitter. Thus, practical high-throughput QAM communication systems exhibit nonlinear and dispersive channel characteristics that must be modeled as a Hammerstein channel. Standard linear equalization becomes inadequate for such Hammerstein communication systems. In this paper, we advocate an adaptive B-Spline neural network based nonlinear equalizer. Specifically, during the training phase, an efficient alternating least squares (LS) scheme is employed to estimate the parameters of the Hammerstein channel, including both the channel impulse response (CIR) coefficients and the parameters of the B-spline neural network that models the HPA’s nonlinearity. In addition, another B-spline neural network is used to model the inversion of the nonlinear HPA, and the parameters of this inverting B-spline model can easily be estimated using the standard LS algorithm based on the pseudo training data obtained as a natural byproduct of the Hammerstein channel identification. Nonlinear equalisation of the Hammerstein channel is then accomplished by the linear equalization based on the estimated CIR as well as the inverse B-spline neural network model. Furthermore, during the data communication phase, the decision-directed LS channel estimation is adopted to track the time-varying CIR. Extensive simulation results demonstrate the effectiveness of our proposed B-Spline neural network based nonlinear equalization scheme.

(How) Do research and administrative duties affect university professors’ teaching?

We analyze the interaction between university professors’ teaching quality and their research and administrative activities. Our sample is a high-quality individual panel data set from a medium size public Spanish university that allows us to avoid several types of biases frequently encountered in the literature. Although researchers teach roughly 20% more than non-researchers, their teaching quality is also 20% higher. Instructors with no research are 5 times more likely than the rest to be among the worst teachers. Over much of the relevant range, we find a nonlinear and positive relationship between research output and teaching quantity on teaching quality. Our conclusions may be useful for decision makers in universities and governments.